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fix norm, fix matrix matrix sub-sum

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Deniz Donmez
2025-09-15 14:13:16 +03:00
parent 1f2b143f84
commit b55ee766a7
1 changed files with 53 additions and 4 deletions
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57
numethods/linalg.py
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@@ -21,6 +21,9 @@ class Vector:
def copy(self) -> "Vector": def copy(self) -> "Vector":
return Vector(self.data[:]) return Vector(self.data[:])
def norm(self) -> Number:
return sum(abs(x) for x in self.data)
def norm_inf(self) -> Number: def norm_inf(self) -> Number:
return max(abs(x) for x in self.data) if self.data else 0.0 return max(abs(x) for x in self.data) if self.data else 0.0
@@ -28,12 +31,14 @@ class Vector:
return sum(x * x for x in self.data) ** 0.5 return sum(x * x for x in self.data) ** 0.5
def __add__(self, other: "Vector") -> "Vector": def __add__(self, other: "Vector") -> "Vector":
assert len(self) == len(other) if len(self) != len(other):
return Vector(a + b for a, b in zip(self.data, other.data)) raise ValueError("Vector dimensions must match for addition")
return Vector([a + b for a, b in zip(self.data, other.data)])
def __sub__(self, other: "Vector") -> "Vector": def __sub__(self, other: "Vector") -> "Vector":
assert len(self) == len(other) if len(self) != len(other):
return Vector(a - b for a, b in zip(self.data, other.data)) raise ValueError("Vector dimensions must match for subtraction")
return Vector([a - b for a, b in zip(self.data, other.data)])
def __mul__(self, scalar: Number) -> "Vector": def __mul__(self, scalar: Number) -> "Vector":
return Vector(scalar * x for x in self.data) return Vector(scalar * x for x in self.data)
@@ -92,6 +97,50 @@ class Matrix:
def col(self, j: int) -> Vector: def col(self, j: int) -> Vector:
return Vector(self.data[i][j] for i in range(self.m)) return Vector(self.data[i][j] for i in range(self.m))
def norm(self) -> Number:
return (
max(sum(abs(self.data[i][j]) for i in range(self.m)) for j in range(self.n))
if self.n > 0
else 0.0
)
def norm_inf(self) -> Number:
return (
max(sum(abs(self.data[i][j]) for j in range(self.n)) for i in range(self.m))
if self.m > 0
else 0.0
)
def norm_fro(self) -> Number:
return (
sum(self.data[i][j] ** 2 for i in range(self.m) for j in range(self.n))
** 0.5
)
def __add__(self, other: "Matrix") -> "Matrix":
if not isinstance(other, Matrix):
raise TypeError("Can only add Matrix with Matrix")
if self.m != other.m or self.n != other.n:
raise ValueError("Matrix dimensions must match for addition")
return Matrix(
[
[self.data[i][j] + other.data[i][j] for j in range(self.n)]
for i in range(self.m)
]
)
def __sub__(self, other: "Matrix") -> "Matrix":
if not isinstance(other, Matrix):
raise TypeError("Can only subtract Matrix with Matrix")
if self.m != other.m or self.n != other.n:
raise ValueError("Matrix dimensions must match for subtraction")
return Matrix(
[
[self.data[i][j] - other.data[i][j] for j in range(self.n)]
for i in range(self.m)
]
)
def transpose(self) -> "Matrix": def transpose(self) -> "Matrix":
return Matrix([[self.data[i][j] for i in range(self.m)] for j in range(self.n)]) return Matrix([[self.data[i][j] for i in range(self.m)] for j in range(self.n)])